Evidence map›Paper›PMID 33917186›Full record

ArticleCancers2021

Systematic Analysis of the Transcriptome Profiles and Co-Expression Networks of Tumour Endothelial Cells Identifies Several Tumour-Associated Modules and Potential Therapeutic Targets in Hepatocellular Carcinoma.

Thomas Mohr, Sonja Katz, Verena Paulitschke, Nadim Aizarani, Alexander Tolios

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.2field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 19 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 4 institutions in 2 countries.

Thomas MohrScienceConsult-DI Thomas Mohr KG, Enzianweg 10a, A-2353 Guntramsdorf, Austria.ORCID 0000-0002-1933-847X
Sonja KatzScienceConsult-DI Thomas Mohr KG, Enzianweg 10a, A-2353 Guntramsdorf, Austria.ORCID 0000-0002-9958-0724
Verena PaulitschkeDepartment of Dermatology, Medical University of Vienna, A-1090 Vienna, Austria.ORCID 0000-0003-0212-9476
Nadim AizaraniMax-Planck-Institute of Immunobiology and Epigenetics, D-79108 Freiburg, Germany.
Alexander ToliosDepartment of Blood Group Serology and Transfusion Medicine, Medical University of Vienna, A-1090 Vienna, Austria.ORCID 0000-0001-9163-7127
Austrian Research Institute for Artificial Intelligence · ATComprehensive Cancer Center Vienna · ATMax Planck Institute of Immunobiology and Epigenetics · DEMedical University of Vienna · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is the sixth most common cancer and the third most common cause of cancer-related death, with tumour associated liver endothelial cells being thought to be major drivers in HCC progression. This study aims to compare the gene expression profiles of tumour endothelial cells from the liver with endothelial cells from non-tumour liver tissue, to identify perturbed biologic functions, co-expression modules, and potentially drugable hub genes that could give rise to novel therapeutic targets and strategies. Gene Set Variation Analysis (GSVA) showed that cell growth-related pathways were upregulated, whereas apoptosis induction, immune and inflammatory-related pathways were downregulated in tumour endothelial cells. Weighted Gene Co-expression Network Analysis (WGCNA) identified several modules strongly associated to tumour endothelial cells or angiogenic activated endothelial cells with high endoglin (

Indexed as

hepatocellular carcinomaliver endothelial cellsnetwork analysistumour associated endothelial cells

Identifiers

PMID33917186
PMCPMC8067977
OpenAlexW3151163502

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.